R Notebook
Enviornment
1 + 100
2^2
7/2
4-1
2*2
3 + 5*2
(3+5)*2
2e2
2/100000
sin(1)
log(1)
exp(0)
1 == 1
1 >= 1
1 < 1
1 != 2
x <- 10
x <- 10
x
x + x
x - 5
x^2
y <- x + x
y
1:5
2^(1:5)
v <- 1:5
2^v
log10(v)
Package managment
installed.packages() Package LibPath
askpass "askpass" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
base "base" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
base64enc "base64enc" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
boot "boot" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
bslib "bslib" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
cachem "cachem" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
class "class" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
cluster "cluster" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
codetools "codetools" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
compiler "compiler" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
curl "curl" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
datasets "datasets" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
digest "digest" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
evaluate "evaluate" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
fastmap "fastmap" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
foreign "foreign" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
fs "fs" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
glue "glue" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
graphics "graphics" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
grDevices "grDevices" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
grid "grid" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
highr "highr" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
htmltools "htmltools" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
jquerylib "jquerylib" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
jsonlite "jsonlite" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
KernSmooth "KernSmooth" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
knitr "knitr" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
lattice "lattice" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
magrittr "magrittr" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
markdown "markdown" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
MASS "MASS" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
Matrix "Matrix" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
memoise "memoise" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
methods "methods" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
mgcv "mgcv" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
mime "mime" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
nlme "nlme" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
nnet "nnet" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
openssl "openssl" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
packrat "packrat" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
parallel "parallel" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
permute "permute" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
R6 "R6" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rappdirs "rappdirs" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rlang "rlang" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rmarkdown "rmarkdown" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rpart "rpart" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rsconnect "rsconnect" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
rstudioapi "rstudioapi" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
sass "sass" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
spatial "spatial" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
splines "splines" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
stats "stats" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
stats4 "stats4" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
stringi "stringi" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
stringr "stringr" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
survival "survival" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
sys "sys" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
tcltk "tcltk" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
tinytex "tinytex" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
tools "tools" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
utils "utils" "/Library/Frameworks/R.framework/Versions/4.2/Resources/library"
Version Priority Depends
askpass "1.1" NA NA
base "4.2.1" "base" NA
base64enc "0.1-3" NA "R (>= 2.9.0)"
boot "1.3-28" "recommended" "R (>= 3.0.0), graphics, stats"
bslib "0.4.0" NA "R (>= 2.10)"
cachem "1.0.6" NA NA
class "7.3-20" "recommended" "R (>= 3.0.0), stats, utils"
cluster "2.1.3" "recommended" "R (>= 3.5.0)"
codetools "0.2-18" "recommended" "R (>= 2.1)"
compiler "4.2.1" "base" NA
curl "4.3.2" NA "R (>= 3.0.0)"
datasets "4.2.1" "base" NA
digest "0.6.29" NA "R (>= 3.3.0)"
evaluate "0.16" NA "R (>= 3.0.2)"
fastmap "1.1.0" NA NA
foreign "0.8-82" "recommended" "R (>= 4.0.0)"
fs "1.5.2" NA "R (>= 3.1)"
glue "1.6.2" NA "R (>= 3.4)"
graphics "4.2.1" "base" NA
grDevices "4.2.1" "base" NA
grid "4.2.1" "base" NA
highr "0.9" NA "R (>= 3.2.3)"
htmltools "0.5.3" NA "R (>= 2.14.1)"
jquerylib "0.1.4" NA NA
jsonlite "1.8.0" NA "methods"
KernSmooth "2.23-20" "recommended" "R (>= 2.5.0), stats"
knitr "1.40" NA "R (>= 3.3.0)"
lattice "0.20-45" "recommended" "R (>= 3.0.0)"
magrittr "2.0.3" NA "R (>= 3.4.0)"
markdown "1.1" NA "R (>= 2.11.1)"
MASS "7.3-57" "recommended" "R (>= 3.3.0), grDevices, graphics, stats, utils"
Matrix "1.4-1" "recommended" "R (>= 3.5.0)"
memoise "2.0.1" NA NA
methods "4.2.1" "base" NA
mgcv "1.8-40" "recommended" "R (>= 3.6.0), nlme (>= 3.1-64)"
mime "0.12" NA NA
nlme "3.1-157" "recommended" "R (>= 3.5.0)"
nnet "7.3-17" "recommended" "R (>= 3.0.0), stats, utils"
openssl "2.0.3" NA NA
packrat "0.8.1" NA "R (>= 3.0.0)"
parallel "4.2.1" "base" NA
permute "0.9-7" NA "R (>= 2.14.0)"
R6 "2.5.1" NA "R (>= 3.0)"
rappdirs "0.3.3" NA "R (>= 3.2)"
rlang "1.0.6" NA "R (>= 3.4.0)"
rmarkdown "2.16" NA "R (>= 3.0)"
rpart "4.1.16" "recommended" "R (>= 2.15.0), graphics, stats, grDevices"
rsconnect "0.8.27" NA "R (>= 3.0.0)"
rstudioapi "0.14" NA NA
sass "0.4.2" NA NA
spatial "7.3-15" "recommended" "R (>= 3.0.0), graphics, stats, utils"
splines "4.2.1" "base" NA
stats "4.2.1" "base" NA
stats4 "4.2.1" "base" NA
stringi "1.7.8" NA "R (>= 3.1)"
stringr "1.4.1" NA "R (>= 3.1)"
survival "3.3-1" "recommended" "R (>= 3.5.0)"
sys "3.4" NA NA
tcltk "4.2.1" "base" NA
tinytex "0.42" NA NA
tools "4.2.1" "base" NA
utils "4.2.1" "base" NA
Imports
askpass "sys (>= 2.1)"
base NA
base64enc NA
boot NA
bslib "grDevices, htmltools (>= 0.5.2), jsonlite, sass (>= 0.4.0),\njquerylib (>= 0.1.3), rlang, cachem, memoise"
cachem "rlang, fastmap"
class "MASS"
cluster "graphics, grDevices, stats, utils"
codetools NA
compiler NA
curl NA
datasets NA
digest "utils"
evaluate "methods"
fastmap NA
foreign "methods, utils, stats"
fs "methods"
glue "methods"
graphics "grDevices"
grDevices NA
grid "grDevices, utils"
highr "xfun (>= 0.18)"
htmltools "utils, digest, grDevices, base64enc, rlang (>= 0.4.10),\nfastmap (>= 1.1.0)"
jquerylib "htmltools"
jsonlite NA
KernSmooth NA
knitr "evaluate (>= 0.15), highr, methods, stringr (>= 0.6), yaml (>=\n2.1.19), xfun (>= 0.29), tools"
lattice "grid, grDevices, graphics, stats, utils"
magrittr NA
markdown "utils, xfun, mime (>= 0.3)"
MASS "methods"
Matrix "methods, graphics, grid, stats, utils, lattice"
memoise "rlang (>= 0.4.10), cachem"
methods "utils, stats"
mgcv "methods, stats, graphics, Matrix, splines, utils"
mime "tools"
nlme "graphics, stats, utils, lattice"
nnet NA
openssl "askpass"
packrat "tools, utils"
parallel "tools, compiler"
permute "stats"
R6 NA
rappdirs NA
rlang "utils"
rmarkdown "bslib (>= 0.2.5.1), evaluate (>= 0.13), htmltools (>= 0.5.1),\njquerylib, jsonlite, knitr (>= 1.22), methods, stringr (>=\n1.2.0), tinytex (>= 0.31), tools, utils, xfun (>= 0.30), yaml\n(>= 2.1.19)"
rpart NA
rsconnect "curl, digest, jsonlite, openssl (>= 2.0.0), packrat (>= 0.6),\nrstudioapi (>= 0.5), tools, yaml (>= 2.1.5)"
rstudioapi NA
sass "fs, rlang (>= 0.4.10), htmltools (>= 0.5.1), R6, rappdirs"
spatial NA
splines "graphics, stats"
stats "utils, grDevices, graphics"
stats4 "graphics, methods, stats"
stringi "tools, utils, stats"
stringr "glue (>= 1.2.0), magrittr, stringi (>= 1.1.7)"
survival "graphics, Matrix, methods, splines, stats, utils"
sys NA
tcltk "utils"
tinytex "xfun (>= 0.29)"
tools NA
utils NA
LinkingTo
askpass NA
base NA
base64enc NA
boot NA
bslib NA
cachem NA
class NA
cluster NA
codetools NA
compiler NA
curl NA
datasets NA
digest NA
evaluate NA
fastmap NA
foreign NA
fs NA
glue NA
graphics NA
grDevices NA
grid NA
highr NA
htmltools NA
jquerylib NA
jsonlite NA
KernSmooth NA
knitr NA
lattice NA
magrittr NA
markdown NA
MASS NA
Matrix NA
memoise NA
methods NA
mgcv NA
mime NA
nlme NA
nnet NA
openssl NA
packrat NA
parallel NA
permute NA
R6 NA
rappdirs NA
rlang NA
rmarkdown NA
rpart NA
rsconnect NA
rstudioapi NA
sass NA
spatial NA
splines NA
stats NA
stats4 NA
stringi NA
stringr NA
survival NA
sys NA
tcltk NA
tinytex NA
tools NA
utils NA
Suggests
askpass "testthat"
base "methods"
base64enc NA
boot "MASS, survival"
bslib "shiny (>= 1.6.0), rmarkdown (>= 2.7), thematic, knitr,\ntestthat, withr, rappdirs, curl, magrittr"
cachem "testthat"
class NA
cluster "MASS, Matrix"
codetools NA
compiler NA
curl "spelling, testthat (>= 1.0.0), knitr, jsonlite, rmarkdown,\nmagrittr, httpuv (>= 1.4.4), webutils"
datasets NA
digest "tinytest, simplermarkdown"
evaluate "covr, ggplot2, lattice, testthat"
fastmap "testthat (>= 2.1.1)"
foreign NA
fs "testthat, covr, pillar (>= 1.0.0), tibble (>= 1.1.0), crayon,\nrmarkdown, knitr, withr, spelling, vctrs (>= 0.3.0)"
glue "covr, crayon, DBI, dplyr, forcats, ggplot2, knitr, magrittr,\nmicrobenchmark, R.utils, rmarkdown, rprintf, RSQLite, stringr,\ntestthat (>= 3.0.0), vctrs (>= 0.3.0), waldo (>= 0.3.0), withr"
graphics NA
grDevices "KernSmooth"
grid NA
highr "knitr, markdown, testit"
htmltools "markdown, testthat, withr, Cairo, ragg, shiny"
jquerylib "testthat"
jsonlite "httr, curl, vctrs, testthat, knitr, rmarkdown, R.rsp, sf"
KernSmooth "MASS, carData"
knitr "markdown, formatR, testit, digest, rgl (>= 0.95.1201),\ncodetools, rmarkdown, htmlwidgets (>= 0.7), webshot, tikzDevice\n(>= 0.10), tinytex, reticulate (>= 1.4), JuliaCall (>= 0.11.1),\nmagick, png, jpeg, gifski, xml2 (>= 1.2.0), httr, DBI (>=\n0.4-1), showtext, tibble, sass, bslib, ragg, gridSVG, styler\n(>= 1.2.0), targets (>= 0.6.0)"
lattice "KernSmooth, MASS, latticeExtra"
magrittr "covr, knitr, rlang, rmarkdown, testthat"
markdown "knitr, RCurl"
MASS "lattice, nlme, nnet, survival"
Matrix "expm, MASS"
memoise "digest, aws.s3, covr, googleAuthR, googleCloudStorageR, httr,\ntestthat"
methods "codetools"
mgcv "parallel, survival, MASS"
mime NA
nlme "Hmisc, MASS, SASmixed"
nnet "MASS"
openssl "curl, testthat (>= 2.1.0), digest, knitr, rmarkdown,\njsonlite, jose, sodium"
packrat "testthat (>= 3.0.0), devtools, httr, knitr, rmarkdown"
parallel "methods"
permute "vegan (>= 2.0-0), testthat (>= 0.5), parallel, knitr,\nrmarkdown, bookdown, sessioninfo"
R6 "testthat, pryr"
rappdirs "roxygen2, testthat (>= 3.0.0), covr, withr"
rlang "cli (>= 3.1.0), covr, crayon, fs, glue, knitr, magrittr,\nmethods, pillar, rmarkdown, stats, testthat (>= 3.0.0), tibble,\nusethis, vctrs (>= 0.2.3), withr"
rmarkdown "digest, dygraphs, fs, rsconnect, downlit (>= 0.4.0), katex\n(>= 1.4.0), sass (>= 0.4.0), shiny (>= 1.6.0), testthat (>=\n3.0.3), tibble, tufte, vctrs, withr (>= 2.4.2)"
rpart "survival"
rsconnect "MASS, RCurl, callr, httpuv, knitr, plumber (>= 0.3.2),\nreticulate, rmarkdown (>= 1.1), shiny, sourcetools, testthat,\nxtable"
rstudioapi "testthat, knitr, rmarkdown, clipr, covr"
sass "testthat, knitr, rmarkdown, withr, shiny, curl"
spatial "MASS"
splines "Matrix, methods"
stats "MASS, Matrix, SuppDists, methods, stats4"
stats4 NA
stringi NA
stringr "covr, htmltools, htmlwidgets, knitr, rmarkdown, testthat"
survival NA
sys "unix (>= 1.4), spelling, testthat"
tcltk NA
tinytex "testit, rstudioapi"
tools "codetools, methods, xml2, curl, commonmark, knitr, xfun, mathjaxr"
utils "methods, xml2, commonmark, knitr"
Enhances
askpass NA
base NA
base64enc "png"
boot NA
bslib NA
cachem NA
class NA
cluster NA
codetools NA
compiler NA
curl NA
datasets NA
digest NA
evaluate NA
fastmap NA
foreign NA
fs NA
glue NA
graphics NA
grDevices NA
grid NA
highr NA
htmltools "knitr"
jquerylib NA
jsonlite NA
KernSmooth NA
knitr NA
lattice "chron"
magrittr NA
markdown NA
MASS NA
Matrix "MatrixModels, graph, SparseM, sfsmisc, igraph, maptools, sp,\nspdep"
memoise NA
methods NA
mgcv NA
mime NA
nlme NA
nnet NA
openssl NA
packrat NA
parallel "snow, nws, Rmpi"
permute NA
R6 NA
rappdirs NA
rlang "winch"
rmarkdown NA
rpart NA
rsconnect NA
rstudioapi NA
sass NA
spatial NA
splines NA
stats NA
stats4 NA
stringi NA
stringr NA
survival NA
sys NA
tcltk NA
tinytex NA
tools NA
utils NA
License License_is_FOSS License_restricts_use OS_type
askpass "MIT + file LICENSE" NA NA NA
base "Part of R 4.2.1" NA NA NA
base64enc "GPL-2 | GPL-3" NA NA NA
boot "Unlimited" NA NA NA
bslib "MIT + file LICENSE" NA NA NA
cachem "MIT + file LICENSE" NA NA NA
class "GPL-2 | GPL-3" NA NA NA
cluster "GPL (>= 2)" NA NA NA
codetools "GPL" NA NA NA
compiler "Part of R 4.2.1" NA NA NA
curl "MIT + file LICENSE" NA NA NA
datasets "Part of R 4.2.1" NA NA NA
digest "GPL (>= 2)" NA NA NA
evaluate "MIT + file LICENSE" NA NA NA
fastmap "MIT + file LICENSE" NA NA NA
foreign "GPL (>= 2)" NA NA NA
fs "MIT + file LICENSE" NA NA NA
glue "MIT + file LICENSE" NA NA NA
graphics "Part of R 4.2.1" NA NA NA
grDevices "Part of R 4.2.1" NA NA NA
grid "Part of R 4.2.1" NA NA NA
highr "GPL" NA NA NA
htmltools "GPL (>= 2)" NA NA NA
jquerylib "MIT + file LICENSE" NA NA NA
jsonlite "MIT + file LICENSE" NA NA NA
KernSmooth "Unlimited" NA NA NA
knitr "GPL" NA NA NA
lattice "GPL (>= 2)" NA NA NA
magrittr "MIT + file LICENSE" NA NA NA
markdown "GPL-2" NA NA NA
MASS "GPL-2 | GPL-3" NA NA NA
Matrix "GPL (>= 2) | file LICENCE" NA NA NA
memoise "MIT + file LICENSE" NA NA NA
methods "Part of R 4.2.1" NA NA NA
mgcv "GPL (>= 2)" NA NA NA
mime "GPL" NA NA NA
nlme "GPL (>= 2)" NA NA NA
nnet "GPL-2 | GPL-3" NA NA NA
openssl "MIT + file LICENSE" NA NA NA
packrat "GPL-2" NA NA NA
parallel "Part of R 4.2.1" NA NA NA
permute "GPL-2" NA NA NA
R6 "MIT + file LICENSE" NA NA NA
rappdirs "MIT + file LICENSE" NA NA NA
rlang "MIT + file LICENSE" NA NA NA
rmarkdown "GPL-3" NA NA NA
rpart "GPL-2 | GPL-3" NA NA NA
rsconnect "GPL-2" NA NA NA
rstudioapi "MIT + file LICENSE" NA NA NA
sass "MIT + file LICENSE" NA NA NA
spatial "GPL-2 | GPL-3" NA NA NA
splines "Part of R 4.2.1" NA NA NA
stats "Part of R 4.2.1" NA NA NA
stats4 "Part of R 4.2.1" NA NA NA
stringi "file LICENSE" NA NA NA
stringr "GPL-2 | file LICENSE" NA NA NA
survival "LGPL (>= 2)" NA NA NA
sys "MIT + file LICENSE" NA NA NA
tcltk "Part of R 4.2.1" NA NA NA
tinytex "MIT + file LICENSE" NA NA NA
tools "Part of R 4.2.1" NA NA NA
utils "Part of R 4.2.1" NA NA NA
MD5sum NeedsCompilation Built
askpass NA "yes" "4.2.0"
base NA NA "4.2.1"
base64enc NA "yes" "4.2.0"
boot NA "no" "4.2.1"
bslib NA "no" "4.2.0"
cachem NA "yes" "4.2.0"
class NA "yes" "4.2.1"
cluster NA "yes" "4.2.1"
codetools NA "no" "4.2.1"
compiler NA NA "4.2.1"
curl NA "yes" "4.2.0"
datasets NA NA "4.2.1"
digest NA "yes" "4.2.0"
evaluate NA "no" "4.2.0"
fastmap NA "yes" "4.2.0"
foreign NA "yes" "4.2.1"
fs NA "yes" "4.2.0"
glue NA "yes" "4.2.0"
graphics NA "yes" "4.2.1"
grDevices NA "yes" "4.2.1"
grid NA "yes" "4.2.1"
highr NA "no" "4.2.0"
htmltools NA "yes" "4.2.0"
jquerylib NA "no" "4.2.0"
jsonlite NA "yes" "4.2.0"
KernSmooth NA "yes" "4.2.1"
knitr NA "no" "4.2.0"
lattice NA "yes" "4.2.1"
magrittr NA "yes" "4.2.0"
markdown NA "yes" "4.2.0"
MASS NA "yes" "4.2.1"
Matrix NA "yes" "4.2.1"
memoise NA "no" "4.2.0"
methods NA "yes" "4.2.1"
mgcv NA "yes" "4.2.1"
mime NA "yes" "4.2.0"
nlme NA "yes" "4.2.1"
nnet NA "yes" "4.2.1"
openssl NA "yes" "4.2.0"
packrat NA "no" "4.2.1"
parallel NA "yes" "4.2.1"
permute NA "no" "4.2.0"
R6 NA "no" "4.2.0"
rappdirs NA "yes" "4.2.0"
rlang NA "yes" "4.2.0"
rmarkdown NA "no" "4.2.1"
rpart NA "yes" "4.2.1"
rsconnect NA "no" "4.2.1"
rstudioapi NA "no" "4.2.0"
sass NA "yes" "4.2.0"
spatial NA "yes" "4.2.1"
splines NA "yes" "4.2.1"
stats NA "yes" "4.2.1"
stats4 NA NA "4.2.1"
stringi NA "yes" "4.2.0"
stringr NA "no" "4.2.0"
survival NA "yes" "4.2.1"
sys NA "yes" "4.2.0"
tcltk NA "yes" "4.2.1"
tinytex NA "no" "4.2.0"
tools NA "yes" "4.2.1"
utils NA "yes" "4.2.1"
[ reached getOption("max.print") -- omitted 2 rows ]#install.packages("vegan", dependencies = TRUE)#library(vegan)#remove.packages("vegan")Getting Help
?plot()help(plot)?"<-"vignette("FAQ-vegan")Warning: vignette ‘FAQ-vegan’ not foundData and their formats
cats <- data.frame(coat = c("calico", "black", "taffy"),
weight = c(2.1,5,3.2),
likes_string = c(1,0,1))catsgetwd()[1] "/Users/josh/Desktop/BIOL PRACTICAL COMPUTING/pratcomp_2022"write.csv(cats, file = "./cats.csv")cats <- read.csv("./data/cats/csv")Warning: cannot open file './data/cats/csv': No such file or directoryError in file(file, "rt") : cannot open the connectioncats$coat[1] "calico" "black" "taffy" cats$weight[1] 2.1 5.0 3.2cats$weight*10[1] 21 50 32log(cats$weight)[1] 0.7419373 1.6094379 1.1631508logweight <- log(cats$weight)
cbind(cats,logweight)cats <- cbind(cats,logweight)catspaste("My cat is ", cats$coat, ", and it weighs ", cats$weight, " kg.", sep="")[1] "My cat is calico, and it weighs 2.1 kg." "My cat is black, and it weighs 5 kg."
[3] "My cat is taffy, and it weighs 3.2 kg." Data types
typeof(cats$coat)[1] "character"typeof(cats$weight)[1] "double"typeof(cats$likes_string)[1] "double"typeof(3.14159)[1] "double"typeof(FALSE)[1] "logical"typeof(TRUE)[1] "logical"typeof(T)[1] "logical"typeof(F)[1] "logical"typeof(cats)[1] "list"class(cats)[1] "data.frame"file.show("./data/cats.csv")Error: File ./data/cats.csv does not exist.cats$likes_string <- as.logical(cats$likes_string)cats$likes_string[1] TRUE FALSE TRUEc("a","b")[1] "a" "b"ab <- c("a", "b")
ab[1] "a" "b"c(ab,"c")[1] "a" "b" "c"c(ab, ab)[1] "a" "b" "a" "b"1:10 [1] 1 2 3 4 5 6 7 8 9 10seq(10) [1] 1 2 3 4 5 6 7 8 9 10z <- seq(10)
head(z, n=3)[1] 1 2 3length(z)[1] 10class(z)[1] "integer"typeof(z)[1] "integer"seq(0,100, by=5) [1] 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100Data Frames
catsstr(cats$coat) chr [1:3] "calico" "black" "taffy"coats <- c("tabby", "tortoiseshell", "tortoiseshell", "black", "tabby")
coats[1] "tabby" "tortoiseshell" "tortoiseshell" "black" "tabby" str(coats) chr [1:5] "tabby" "tortoiseshell" "tortoiseshell" "black" "tabby"factor(coats)[1] tabby tortoiseshell tortoiseshell black tabby
Levels: black tabby tortoiseshellcategories <- factor(coats)
class(coats)[1] "character"class(categories)[1] "factor"str(categories) Factor w/ 3 levels "black","tabby",..: 2 3 3 1 2Lists
list_example <- list(title="Numbers", numbers = 1:10, data=TRUE)list_example$title
[1] "Numbers"
$numbers
[1] 1 2 3 4 5 6 7 8 9 10
$data
[1] TRUEanother_list <- list(1, "a",TRUE, 1+1i)
another_list[[1]]
[1] 1
[[2]]
[1] "a"
[[3]]
[1] TRUE
[[4]]
[1] 1+1itypeof(list_example)[1] "list"class(list_example)[1] "list"typeof(cats)[1] "list"class(cats)[1] "data.frame"data.frame(list_example)catscats[,2][1] 2.1 5.0 3.2cats[3,]cats[2:3,c(1,3)]Matricies
matrix_example <- matrix(0, ncol=5, nrow=3)matrix_example [,1] [,2] [,3] [,4] [,5]
[1,] 0 0 0 0 0
[2,] 0 0 0 0 0
[3,] 0 0 0 0 0class(matrix_example)[1] "matrix" "array" typeof(matrix_example)[1] "double"str(matrix_example) num [1:3, 1:5] 0 0 0 0 0 0 0 0 0 0 ...dim(matrix_example)[1] 3 5ncol(matrix_example)[1] 5nrow(matrix_example)[1] 3class(data.frame(matrix_example))[1] "data.frame"df_example <- data.frame(matrix_example)
df_exampleSubsetting
p <- c(2.3,6.9,4.0,24.3,2)
p[1] 2.3 6.9 4.0 24.3 2.0names(p) <- c('a','b','c','d','e')
p a b c d e
2.3 6.9 4.0 24.3 2.0 p[2:4] b c d
6.9 4.0 24.3 p[c(1,5)] a e
2.3 2.0 p[c(1,1,1,3,5,5)] a a a c e e
2.3 2.3 2.3 4.0 2.0 2.0 p[6]<NA>
NA p[-3] a b d e
2.3 6.9 24.3 2.0 p[c(-1,-5)] b c d
6.9 4.0 24.3 p[-(2:4)] a e
2.3 2.0 p[c('a','c')] a c
2.3 4.0 p[c(T,F,T,F,T)] a c e
2.3 4.0 2.0 p[names(p) != 'c'] a b d e
2.3 6.9 24.3 2.0 Factors
f <- factor(c('a','b','c','d','e'))
f[1] a b c d e
Levels: a b c d ef[f == 'a'][1] a
Levels: a b c d ef[1:3][1] a b c
Levels: a b c d ef[f %in% c('b','c')][1] b c
Levels: a b c d ef[-3][1] a b d e
Levels: a b c d ef2 <- c('a','a','b','c','c')
f2[1] "a" "a" "b" "c" "c"f2[f2 == 'a'][1] "a" "a"f2[f2 %in% c('a','c')][1] "a" "a" "c" "c"Matricies Resumed
set.seed(21)
m <- matrix(rnorm(6*4), ncol=4, nrow=6)
m [,1] [,2] [,3] [,4]
[1,] 0.7930132 -1.570199630 -0.5484056 -0.78464137
[2,] 0.5222513 -0.934905667 0.1725495 -0.42569229
[3,] 1.7462222 0.063493345 0.5628531 0.39299759
[4,] -1.2713361 -0.002393336 1.5118180 0.03675713
[5,] 2.1973895 -2.276781240 0.6590252 -1.03208366
[6,] 0.4331308 0.757412225 1.1220281 -1.26486147m[3:4, c(3,1)] [,1] [,2]
[1,] 0.5628531 1.746222
[2,] 1.5118180 -1.271336m[,c(3,4)] [,1] [,2]
[1,] -0.5484056 -0.78464137
[2,] 0.1725495 -0.42569229
[3,] 0.5628531 0.39299759
[4,] 1.5118180 0.03675713
[5,] 0.6590252 -1.03208366
[6,] 1.1220281 -1.26486147Lists revisted
xlist <- list(a="BIOL48006220",b=seq(1,10,by = 0.5), data="Grade")
xlist$a
[1] "BIOL48006220"
$b
[1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0
$data
[1] "Grade"xlist[1:2]$a
[1] "BIOL48006220"
$b
[1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0xlist['a']$a
[1] "BIOL48006220"xlist[['a']][1] "BIOL48006220"xlist['b']$b
[1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0xlist[['b']] [1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0xlist$b [1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0Data Frames Revisited
gp <- read.csv('forest_area_sq_km.csv')head(gp, n=10L)head(gp[3], n=10L)nrow(gp)[1] 214head(gp[["country"]], 10L) [1] "Aruba" "Afghanistan" "Angola"
[4] "Albania" "Andorra" "United Arab Emirates"
[7] "Argentina" "Armenia" "American Samoa"
[10] "Antigua and Barbuda" gp$X2001 [1] "4.2" "12.1k" "766k" "7720" "160" "3110" "327k" "3320" "177" "93.2"
[11] "1.31M" "38.4k" "9960" "1940" "6720" "40.4k" "71.2k" "19.1k" "34.5k" "4"
[21] "5100" "21.1k" "83.4k" "14.5k" "10" "547k" "5.43M" "63" "3940" "26.3k"
[31] "174k" "228k" "3.48M" "8.68" "12k" "160k" "1.82M" "48.7k" "215k" "1.43M"
[41] "222k" "623k" "408" "403" "28.6k" "25.3k" "129" "1720" "26.4k" "114k"
[51] "56" "479" "5750" "19.9k" "16.5k" "136k" "605" "11.1k" "174k" "22.6k"
[61] "184k" "224k" "10.2k" "155k" "0.8" "639" "237k" "34.6" "29.8k" "27.7k"
[71] "86.7k" "0" "68.6k" "3460" "21.3k" "26k" "36.6k" "177" "2.2" "41.1k"
[81] "240" "186k" "67.4k" "18.9k" "3800" "19.5k" "1.01M" "680k" "6480" "96k"
[91] "8190" "328" "1530" "85k" "5280" "975" "249k" "31.4k" "38.9k" "11.9k"
[101] "107k" "11.8" "110" "64.6k" "51.3" "173k" "1380" "81.6k" "2170" "210"
[111] "67" "21.5k" "345" "20.5k" "871" "32.7k" "10" "55.4k" "0" "3500"
[121] "129k" "8.2" "681k" "94" "9580" "133k" "3.5" "342k" "6260" "142k"
[131] "316" "407k" "4110" "412" "30k" "195k" "79.2k" "8380" "13k" "246k"
[141] "51.6k" "3620" "" "121k" "58.2k" "0" "98.5k" "30" "44.3k" "44.2k"
[151] "750k" "72.2k" "398" "363k" "91.1k" "4420" "64.1k" "32.8k" "223k" "91.2"
[161] "1490" "0" "64k" "8.1M" "2830" "9770" "" "87.8k" "172" "25.4k"
[171] "28.9k" "6650" "10" "73.6k" "24.8k" "" "583" "153k" "19k" "12.4k"
[181] "281k" "4760" "" "337" "4440" "105" "61.9k" "12.6k" "192k" "4100"
[191] "41.3k" "9460" "89.5" "2360" "6720" "203k" "10" "529k" "30.8k" "95.2k"
[201] "14.4k" "3.05M" "30.4k" "285" "488k" "36.6" "201" "121k" "4420" "1700"
[211] "5490" "177k" "470k" "183k" gp[c(1,3), 2:5]gp[ which(gp$X1989 <= 100 & gp$X2019 >= 100),]Conditionals and Flow
n <- 10
if (n < 10) {
print("n is less than 10")
} else if (n > 10) {
print("n is greater than 10")
} else {
print("n is equal to 10")
}[1] "n is equal to 10"for (n in seq(0,20)) {
if (n < 10) {
print("n is less than 10")
} else if (n > 10) {
print("n is greater than 10")
} else {
print("n is equal to 10")
}
} [1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is less than 10"
[1] "n is equal to 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"
[1] "n is greater than 10"g <- 0
while (g <=10) {
print(paste(g,"is less than or equal to 10"))
g <- g+1
}[1] "0 is less than or equal to 10"
[1] "1 is less than or equal to 10"
[1] "2 is less than or equal to 10"
[1] "3 is less than or equal to 10"
[1] "4 is less than or equal to 10"
[1] "5 is less than or equal to 10"
[1] "6 is less than or equal to 10"
[1] "7 is less than or equal to 10"
[1] "8 is less than or equal to 10"
[1] "9 is less than or equal to 10"
[1] "10 is less than or equal to 10"Plotting and Figures
install.packages("ggplot2")also installing the dependencies ‘cli’, ‘colorspace’, ‘utf8’, ‘farver’, ‘labeling’, ‘lifecycle’, ‘munsell’, ‘RColorBrewer’, ‘viridisLite’, ‘fansi’, ‘pillar’, ‘pkgconfig’, ‘vctrs’, ‘gtable’, ‘isoband’, ‘scales’, ‘tibble’, ‘withr’
trying URL 'https://cran.rstudio.com/bin/macosx/contrib/4.2/cli_3.4.1.tgz'
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The downloaded binary packages are in
/var/folders/_0/6sf9j_5d6gs3m4rcg_7lqy1r0000gn/T//RtmpZ5guiU/downloaded_packageslibrary(ggplot2)forestdata <- read.csv('forest_area_sq_km.csv')
head(forestdata)ggplot(data=forestdata, mapping=aes(x=X1989, y=X2019)) + geom_point()
gp <- read.csv('gapminder_all.csv')
gpggplot(data=gp, mapping=aes(x=gdpPercap_1952, y=pop_1952)) + geom_point()
ggplot(data=gp, mapping=aes(x=gdpPercap_2002, y=pop_2002)) + geom_point()
gapminder <- read.csv("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder_data.csv")
head(gapminder)ggplot(data=gapminder, mapping=aes(x=gdpPercap, y=lifeExp)) + geom_point()
ggplot(data=gapminder, mapping=aes(x=year, y=lifeExp, by=country, color=continent)) + geom_line()
ggplot(data=gapminder, mapping=aes(x=year, y=lifeExp, by=country)) + geom_line(mapping = aes(color=continent)) + geom_point()
ggplot(data=gapminder, mapping=aes(x=gdpPercap, y=lifeExp)) + geom_point()
ggplot(data=gapminder, mapping=aes(x=gdpPercap, y=lifeExp)) + geom_point(alpha=0.25) + scale_x_log10()
ggplot(data=gapminder, mapping=aes(x=gdpPercap, y=lifeExp)) + geom_point(alpha=0.25, color="purple", size = 0.9, pch = 9) + scale_x_log10() + geom_smooth(method=lm, color="gold", size=1.25)
africas <- gapminder[gapminder$continent == "Africa", ]
head(africas)ggplot(data=africas, mapping = aes(x=year, y=lifeExp)) +
geom_line(color = 'blue') +
facet_wrap( ~ country) +
theme(axis.text.x = element_text(angle = 90)) +
labs(
x = "year",
y = "life Expentency",
title = "Life Expectency Over Time in African Countries"
)
AfricanLifeExp <- ggplot(data=africas, mapping = aes(x=year, y=lifeExp)) +
geom_line(color = 'blue') +
facet_wrap( ~ country) +
theme(axis.text.x = element_text(angle = 90)) +
labs(
x = "year",
y = "life Expentency",
title = "Life Expectency Over Time in African Countries"
)ggsave(filename = "AfricanLifeExp.png", plot = AfricanLifeExp, width = 24, height = 40, dpi = 300, units = "cm")pdf(file = "AfricanLifeExp.pdf", width = 24, height = 40)
plot(AfricanLifeExp)
dev.off()null device
1 write.table(gapminder, file="gapminder_web.csv", sep = ",")write.csv(africas, file="gapminder_web_africas.csv")Statistics
Additional ways of importing/reading data
rand <- c(12, 54, 33, 98, 65)
rand[1] 12 54 33 98 65sum(rand)[1] 262length(rand)avg.rand <- sum(rand)/length(rand)
avg.rand[1] 52.4mean(rand)[1] 52.4sort(rand)[1] 12 33 54 65 98min(rand)[1] 12max(rand)[1] 98cumsum(rand)[1] 12 66 99 197 262diff(rand)[1] 42 -21 65 -33rand[2][1] 54rand*2[1] 24 108 66 196 130pedes <- scan()pedesAnalyses
univariate statistics
- Catoegorical Data
- Barplots
beer <- c(3, 4, 1, 1, 3, 4, 3, 3, 1, 3, 2, 1, 2, 1, 2, 3, 2, 3, 1, 1, 1, 1, 4, 3, 1)
length(beer)[1] 25barplot(beer)
barplot(table(beer), xlab="Beer", ylab="frequency") # Counts
barplot(table(beer)/length(beer), xlab="Beer", ylab="Proportion") # Proportions instead of frequencies
- Pie Charts
pie(table(beer), main="Beer preferrence by students")
- Numerical Data
- Stem-and-lead Plots
stem(pedes)Error in stem(pedes) : object 'pedes' not found- Strip
stripchart(pedes, method="stack")Error in stripchart(pedes, method = "stack") : object 'pedes' not found- Measures of Center
- Mean
##mean(pedes)mean(gapminder2$lifeExp)Error in mean(gapminder2$lifeExp) : object 'gapminder2' not found- Median
median(pedes)median(gapminder$lifeExp)with(gapminder, median(lifeExp))- Mode
which(table(pedes) == max(table(pedes)))- Variation
- Range
range(pedes)diff(range(pedes))- variance
var(pedes)sd(pedes)C. IQRs
IQR(pedes)scale(pedes)- summary
summary(pedes)- Plot
- histograms
##hist(pedes, breaks="scott")##hist(pedes, breaks+"scott", prob=TRUE)#hist(pedes, breaks="scotts", prob=T)
##plot(density(pedes))- Box plots
#boxplot(pedes)#summary(boxplot(pedes))Bivariate and multivariant
spid.gen <- read.csv("data/spider_genitalia.csv", header = T)Warning: cannot open file 'data/spider_genitalia.csv': No such file or directoryError in file(file, "rt") : cannot open the connection##bxoplot(spid.gen$left.bulb ~ spid.gen$right.bulb)##plot(spid.gen$left.bulb ~ spid.gen$right.bulb)plot(spid.gen$left.bulb ~ spid.gen$right.bulb, pch = as.character(spid.gen$habitat))Error in FUN(X[[i]], ...) : object 'spid.gen' not foundC. Linear regression
gen.reg <- lm(spid.gen$left.bulb ~ spid.gen$right.bulb)Error in eval(predvars, data, env) : object 'spid.gen' not foundsummary(gen.reg)Error in summary(gen.reg) : object 'gen.reg' not found###plot(spid.gen$left.bulb ~ spid.gen$right.bulb, pch + as.character(spid.gen$habitat))
##abline(gen.reg)- Correlation Coefficients & Soearman Rank Correlation
cor.gen <- with(spid.gen, cor(left.bulb, right.bulb))Error in with(spid.gen, cor(left.bulb, right.bulb)) :
object 'spid.gen' not found##spearman.cor.gen <- with(spid.gen, cor(left.bulb, right.bulb, methof"spearman"))
##spearman.cor.gen^2- residuals
#####residuals(gen.reg)- transformation
#3plot(spid.gen$left.bulb^2~spid.gen$right.bulb)- Comparing Discrete Treatment Effects a. chi-squared
obs_weighted <- c(4,15,6,15,18,2)
obs_fair <- c(10,10,10,10,10,10)
exp <- c(.16,.17,.16,.17,.17,.17)
chisq.test(obs_weighted, p=exp)
chisq.test(obs_fair, p=exp)- T-tests
#H0 - true mean is equal to 0, but you can set true mean to other values with mu=
##t.test(spid.gen$carapace.length)
##t.test(spid.gen$carapace.length, mu=29)#habitat.t2 <- t.test(spid.gen$carapace.length~spid.gen$habitat)
#habitat.t2#habitat.tless <- t.test(spid.gen$left.bulb, alternative = "less")
#habitat.tless#habitat.tgreater <- t.test(spid.gen$left.bulb, alternative = "greater")
#habitat.tgreaterplot(1:25, rep(0.25,25), pch=1:25, col=1:25, ylim=c(0,6), cex=2, ylab="Line types (lty) 1 to 6", xlab="Plotting character (pch) 1 to 25 and colours (col) 1 to 8", main="Line types (lty), plotting characters (pch), \nand colors (col) for plot and xyplot", lab=c(25,7,2))
points(1:8, rep(0.5,8), pch=20, col=1:8, cex=4)
abline(h=1:6, lty=1:6, col=1:6, lwd=3)
pdf("./DATA/PlotCheatSheet.pdf")Error in pdf("./DATA/PlotCheatSheet.pdf") :
cannot open file './DATA/PlotCheatSheet.pdf'Looping and Conditionals
- If then statments
x <- 0
if(x > 0){
print("positive number")
} else if (x < 0) {
print("negativce number")
} else
print("zero")[1] "zero"a <- c(5,7,2,9)
ifelse(a %% 2 == 0, "even", "odd")[1] "odd" "odd" "even" "odd" - For loops
z <- c(2,5,3,7,8,9,11,7)
count <- 0
for (val in z) {
if(val %% 2 == 0) count = count+1
}
print(count)[1] 2- while statement
i <- 1
while (i < 5) {
print(i)
i = i+1
}[1] 1
[1] 2
[1] 3
[1] 4- Interruptions
x <- 1:5
for (val in x) {
if (val == 3) {
break
}
print(val)
}[1] 1
[1] 2x <- 1:5
for (val in x) {
if (val == 3) {
next
}
print(val)
}[1] 1
[1] 2
[1] 4
[1] 5x <- 1:5
repeat {
print(x)
x = x+1
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[1] 1190 1191 1192 1193 1194randomization and dataset management (short)
- dataset managment
B <- matrix(
c(2,3,4,1,5,98),
nrow=3,
ncol=2
)
B [,1] [,2]
[1,] 2 1
[2,] 3 5
[3,] 4 98t(B) [,1] [,2] [,3]
[1,] 2 3 4
[2,] 1 5 98C <- matrix(
c(7,4,2),
nrow = 3,
ncol = 1
)
C [,1]
[1,] 7
[2,] 4
[3,] 2BC <- cbind(B,C)
BC [,1] [,2] [,3]
[1,] 2 1 7
[2,] 3 5 4
[3,] 4 98 2c(B)[1] 2 3 4 1 5 98- Ranomizations
# rnorm(n, mean, sd)
# sample(x, size, replace = FALSE, prob = NULL)ndist <- rnorm(100, 50, 10)
ndist [1] 47.73035 57.45589 53.32819 38.75960 42.93869 42.72456 31.65686 45.92312 50.26861
[10] 59.11629 66.34346 50.60686 68.47573 50.80125 64.18556 64.58616 50.55877 34.82759
[19] 49.51421 47.85643 70.95818 52.02323 55.17724 66.78143 53.85245 37.18113 44.17849
[28] 67.74119 47.89328 46.47893 55.85172 60.13685 49.77431 40.96845 59.07773 61.61943
[37] 45.42047 59.27957 28.97065 33.22833 67.65656 57.94447 45.16130 69.28359 46.15884
[46] 34.13323 52.14302 38.61718 54.89414 32.47363 55.01017 50.86756 51.91074 58.31839
[55] 43.20968 52.95862 61.12166 53.62590 47.29085 48.03054 50.66955 41.32198 46.37994
[64] 38.60450 41.84629 63.10246 47.41639 56.06265 53.13448 50.53603 61.28254 44.41867
[73] 65.35959 49.37554 50.21575 29.10173 41.89111 20.56210 49.81204 46.45320 50.35570
[82] 54.94119 43.40192 60.01142 60.72084 57.55766 35.44535 59.42871 31.29725 47.46728
[91] 47.07438 52.18768 36.44931 48.77273 45.48135 50.97248 46.81898 44.16238 50.67285
[100] 53.55466mean(ndist)[1] 49.99382sd(ndist)[1] 10.0121hist(ndist)
sample(ndist, 10) [1] 47.07438 43.20968 52.18768 69.28359 50.60686 59.27957 46.37994 57.55766 65.35959
[10] 47.73035test <- 1:100
test [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
[22] 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
[43] 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
[64] 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84
[85] 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100sample(test, 50, replace = FALSE) [1] 47 56 87 91 78 50 88 92 79 32 74 85 35 55 59 60 3 75 96 38 90 52
[23] 73 45 57 99 12 93 21 23 26 86 95 43 49 61 84 14 7 28 41 34 100 5
[45] 19 4 94 9 37 98sample(test, 50, replace = TRUE) [1] 8 86 90 46 62 78 75 12 84 4 61 94 85 42 80 7 22 46 51 21 82 58 15 92 40 44 54 45 13
[30] 95 24 98 64 92 3 71 96 19 63 1 76 85 4 34 65 21 73 72 95 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